To achieve a robust FL system without sacrificing privacy, the server in FedGAN only asks clients to report their loss along with the model parameters of the generator and perform outlier detection on the server-side. Again, in the FL setting for the medical applications, we assume all the clients' training protocol and reported value is regularized by the launched trustworthy software [1]}, thus the shared information is trusted.
